The Institute of Medicine has identified prevention of birth defects as one of six priorities for the nation's[unreadable] health because annually, 150,000 infants (1% - 3% of all U.S. births) are born with some form of physical or[unreadable] mental birth defect. It is estimated that each year, 12 million US women use medications that increase the risk[unreadable] of birth defects. With concurrent use of contraception, birth defects associated with these medications can be[unreadable] prevented. Unfortunately, when prescribing these medications, clinicians rarely counsel women about[unreadable] contraception, and approximately 6% of US pregnancies are exposed to medications that may increase risk of[unreadable] birth defects. As Health IT has improved the safety of medication management in some healthcare settings, we[unreadable] propose to develop and then rigorously evaluate ways computers may be able to help doctors counsel women[unreadable] about preventing birth defects caused by use of certain medications. To better understand what information[unreadable] about risk of medication-induced birth defects would be most useful to primary care clinicians and their[unreadable] patients, we will begin this project by conducting a series of focus groups with clinicians and patients seen in[unreadable] academic and community-based practices. Data from these discussions will help refine the two Health IT[unreadable] interventions we will develop. We will evaluate the impact of each of these interventions using a factorial[unreadable] design randomized controlled trial. In the first trial, we will compare multi-faceted decision support[unreadable] (intervention) to streamlined clinical alerts (control). In the second trial, we will evaluate whether collecting[unreadable] machine-actionable information about women?s risk of pregnancy using a networked tablet computer[unreadable] (intervention) is superior to the way clinicians usually collect this information (control).[unreadable] Over the course of 1 year, we will abstract data from the electronic medical record when study[unreadable] clinicians prescribe teratogenic medications (N=1500), conduct phone interviews with women (N=800)[unreadable] prescribed medications by participating clinicians, and survey participating clinicians (N=100) about their[unreadable] satisfaction with the decision support they receive. We will use this data to confirm our hypotheses that[unreadable] clinicians in the intervention groups will (1) prescribe fewer teratogenic medications, (2) be more likely to[unreadable] prescribe contraception when a teratogenic medication is prescribed, (3) have more patients report satisfaction[unreadable] with the counseling they received, and (4) report more satisfaction with the decision support they received.[unreadable] This evaluation will provide much-needed information on how Health IT can best be harnessed to prevent[unreadable] medication-induced birth defects nationwide. In addition, the Health IT intervention shown to be most effective[unreadable] will be disseminated within the University of Pittsburgh Medical Center, which provides 3 million outpatient[unreadable] visits each year.[unreadable]